I Tested the 3 Major Terminal AI Agents—And This Is My Winner
In the world of software development, we're in a constant race to optimize our workflows. AI tools like GitHub Copilot were game-changers inside the editor, but the new frontier—the one that truly promises a quantum leap in productivity—is the terminal.
My motivation for diving into this ecosystem is clear: I want to boost my productivity as a developer. I see these tools as a "small army of junior developers" at my disposal, capable of handling repetitive tasks or generating boilerplate so I can focus on architecture, business logic, and complex problems.
With that mission in mind, I put the three major contenders of the moment to the test: Anthropic's Claude Code, the model-agnostic OpenCode, and Google's official Gemini CLI.
Getting Started: A Surprisingly Smooth Beginning
First things first: getting started with any of these three tools is incredibly simple. I used npm to install them, but they all offer other methods that get you up and running in your terminal in minutes. There's no fuss and no barrier to entry, which is always appreciated.
A Deep Dive: My Experience with Each Agent
This is where things get interesting, and the differences become night and day.
1. Claude Code: The Agent with "Magic" Under the Hood
I have to say it outright: of the three, Claude Code was the only one that truly amazed me. I don't know what magic they've baked into it, but it performs spectacularly well for virtually any task I've thrown at it.
Its greatest superpower is its workflow: first, it plans, then it acts. Having tested visual coding assistants—especially my favorite, Cline—I was quite skeptical about agents in the terminal, but this one completely blew me away right from the start.
Just as with Cline, which I covered in a previous post, instead of blindly starting to write code, Claude Code gives you the option to review a detailed plan. I strongly recommend you use this feature for any significant task. It outlines the steps it will take, the files it will create or modify, and the commands it will execute. You can discuss this plan, adjust it, and once you agree, give it the green light to get to work. This ability to collaborate on the strategy is, simply put, the best I've seen in a tool of this kind.
I've used it to create projects from scratch, giving it all the necessary context, and the experience has been fantastic. Obviously, you still need to review its work, but I consider that a normal and necessary step with any current AI. Furthermore, its integration with the Model Context Protocol (MCP) servers I use is flawless.
Of course, not all that glitters is gold. Claude Code works wonders, but one of the trade-offs is being tied to Anthropic's models. That said, it's not a huge downside, as their models are exceptional for coding.
Finally, if you're as thrilled with Claude Code as I am, here are a few links to help you enjoy it even more.
- The classic "Awesome" repository with interesting resources.
hesreallyhim
- Several courses for more in-depth details on Claude Code.
2. OpenCode: The Swiss Army Knife of Flexibility
If I had to pick a runner-up, it would be OpenCode. Its main advantage is one that no other contender has: it's model-agnostic.
This is its winning ticket. With OpenCode, you aren't tied to a single provider. You can use models from Anthropic, Google, OpenAI, or connect to OpenRouter for access to dozens of options. This versatility is a massive point in its favor, especially if you need to adapt to different projects and budgets.
I haven't used this agent extensively because its most notable weakness is its integration with MCP servers. For me, these are quite important as I use them heavily to enrich the working context. In my tests, this integration failed frequently and needs significant improvement.
3. Gemini CLI: The Power of a Giant Context Window
In the last place of my personal ranking is Gemini CLI. Although it never gave me a "wow" moment that left me speechless, it has an undeniable technical advantage: it uses Google's Gemini models, which offer the largest context window on the market (though that might change soon: https://www.anthropic.com/news/1m-context).
This is tremendously useful for tasks that require understanding a large amount of code or documentation. You can feed it entire codebases and trust that it will grasp the interconnections. It's a very strong selling point.
Unfortunately, like OpenCode, I found that its integration with MCP servers has a long way to go.
The Final Verdict: My Choice as a Developer
After several weeks of intensive testing, my final choice has a clear order:
- First Place: Claude Code.
- Second Place (Tie): OpenCode and Gemini CLI.
Right now, Claude Code is in a league of its own. Its ability to plan, collaborate, and reliably execute complex tasks makes it the ultimate AI assistant for the terminal. It's the leader of my "army of junior devs."
OpenCode and Gemini CLI are very capable tools, but for different reasons. OpenCode's flexibility is its biggest draw, while Gemini's massive context window gives it a unique edge for certain types of tasks. Both are excellent, but they need to polish their integrations to compete head-to-head with the user experience that Claude offers.
My final recommendation is:
- If you're looking for the most powerful and polished tool on the market and don't mind being within a proprietary ecosystem, go for Claude Code without hesitation.
- If you value freedom, control, and the ability to switch AI models based on your needs, OpenCode is your best ally.
- If you work with very large projects and need the largest possible context window, or simply want a powerful entry point into the world of terminal agents, Gemini CLI is a fantastic option.
The AI revolution in the terminal is here, and it's here to stay.
What about you? Have you tried these agents? Which one is your favorite, or is there one you think I missed? Let me know in the comments or find me on social media!
P.S. A New Contender on the Radar: Cursor CLI
The world of AI tools moves at breakneck speed. Just as I was finishing this post, I came across another project that deserves a special mention: Cursor CLI.
For those unfamiliar, Cursor is a very popular "AI-first" code editor, and this is its command-line version. The promise is very appealing: the ability to use all the intelligence and context of your codebase that the editor already has, but directly from the terminal.
Looking at its documentation, I was particularly struck by its cursor --edit command, which allows for "agentic" edits on files—something along the lines of what I loved so much about Claude Code.
I haven't tested it thoroughly yet, but I'm adding it to my to-do list. It definitely seems like a competitor to watch in this space.
Have you tried it? I'd love to hear your thoughts in the comments.